Clinical Pharmacology of Tafenoquine for the radical cure of vivax malaria
James Watson
2022-07-18
TODO:
- Maybe get rid of the mgcv fits - doesn’t add much
- Do all glms in rstanarm
- Run with updated PK output
Preambule
Load data
##
## DETECTIVE_Ph2 DETECTIVE_Ph3 GATHER
## 329 522 251## TQ doses in data:##
## No Radical Cure PQ15 TQ100 TQ300 TQ50
## 186 265 56 482 55
## TQ600
## 56## [1] 482## [1] 7.692307## [1] 4.929577## 27 patients were lost to follow-up before 1 month## 39 patients were lost to follow-up before 4 months## 125 patients were lost to follow-up before 6 months##
## 0 1
## 775 298##
## 0 1
## 713 360Data summaries
Kaplan Meier time to recurrence
## [1] 186 170 379 56 44 265
##
## [0,0.01) [0.01,3.75) [3.75,6.25) [6.25,8.75) [8.75,15] PQ
## 186 170 379 56 44 265##
## [0,0.01) [0.01,3.75) [3.75,6.25) [6.25,8.75) [8.75,15] PQ
## Brazil 58 61 105 6 3 82
## Cambodia 10 0 16 3 0 9
## Colombia 0 0 13 0 0 6
## Ethiopia 14 0 21 7 0 13
## India 10 21 8 4 7 6
## Peru 62 56 140 21 18 93
## Philippines 1 0 3 0 0 2
## Thailand 31 32 48 11 16 39
## Vietnam 0 0 25 4 0 15## Range of mg/kg weights:## [1] 0.55 14.29## Median number of methb measurements is 12 (range 2 to 19)##
## 0 1
## 775 298##
## 0 1
## [0,0.01) 81 101
## [0.01,3.75) 112 57
## [3.75,6.25) 289 79
## [6.25,8.75) 50 4
## [8.75,15] 43 0
## PQ 200 57## Dose (mg) Rec 4 mths (%) n
## 1 [0,0.01) 55.5 182.0
## 2 [0.01,3.75) 33.7 169.0
## 3 [3.75,6.25) 21.5 368.0
## 4 [6.25,8.75) 7.4 54.0
## 5 [8.75,15] 0.0 43.0
## 6 PQ 22.2 257.0CYP2D6
##
## FALSE TRUE
## 716 384##
## 0 0.5 1 1.5 2
## *1/*1 0 0 0 0 407
## *1/*10 0 0 0 56 0
## *1/*17 0 0 0 34 0
## *1/*3 0 0 3 0 0
## *1/*4 0 0 62 0 0
## *1/*41 0 0 0 27 0
## *1/*5 0 0 24 0 0
## *1/*6 0 0 2 0 0
## *1/*9 0 0 0 10 0
## *10/*10 0 0 35 0 0
## *10/*17 0 0 1 0 0
## *10/*41 0 0 8 0 0
## *17/*17 0 0 3 0 0
## *17/*41 0 0 3 0 0
## *3/*4 3 0 0 0 0
## *3/*9 0 1 0 0 0
## *4/*10 0 1 0 0 0
## *4/*17 0 2 0 0 0
## *4/*4 2 0 0 0 0
## *4/*41 0 7 0 0 0
## *4/*5 3 0 0 0 0
## *4/*9 0 1 0 0 0
## *41/*41 0 0 3 0 0
## *5/*10 0 14 0 0 0
## *5/*41 0 1 0 0 0
## *5/*5 1 0 0 0 0
## *5/*9 0 1 0 0 0
## *9/*41 0 0 1 0 0## CYP2D6 allele frequencies:##
## *1 *10 *17 *3 *4 *41 *5 *6 *9
## 72.1 10.5 3.2 0.5 5.8 3.7 3.1 0.1 1.0##
## 0 0.5 1 1.5 2
## 0 6 0 0 0 0
## 0.25 0 15 0 0 0
## 0.5 3 12 35 0 0
## 0.75 0 0 9 0 0
## 1 0 1 96 0 0
## 1.25 0 0 0 56 0
## 1.5 0 0 5 71 0
## 2 0 0 0 0 407## Activity Score
## CYP2D6 Genotype 0 0.25 0.5 0.75 1 1.25 1.5 2
## *1/*1 0 0 0 0 0 0 0 407
## *1/*10 0 0 0 0 0 56 0 0
## *1/*17 0 0 0 0 0 0 34 0
## *1/*3 0 0 0 0 0 0 3 0
## *1/*4 0 0 0 0 62 0 0 0
## *1/*41 0 0 0 0 0 0 27 0
## *1/*5 0 0 0 0 24 0 0 0
## *1/*6 0 0 0 0 0 0 2 0
## *1/*9 0 0 0 0 0 0 10 0
## *10/*10 0 0 35 0 0 0 0 0
## *10/*17 0 0 0 1 0 0 0 0
## *10/*41 0 0 0 8 0 0 0 0
## *17/*17 0 0 0 0 3 0 0 0
## *17/*41 0 0 0 0 3 0 0 0
## *3/*4 0 0 3 0 0 0 0 0
## *3/*9 0 0 0 0 1 0 0 0
## *4/*10 0 1 0 0 0 0 0 0
## *4/*17 0 0 2 0 0 0 0 0
## *4/*4 2 0 0 0 0 0 0 0
## *4/*41 0 0 7 0 0 0 0 0
## *4/*5 3 0 0 0 0 0 0 0
## *4/*9 0 0 1 0 0 0 0 0
## *41/*41 0 0 0 0 3 0 0 0
## *5/*10 0 14 0 0 0 0 0 0
## *5/*41 0 0 1 0 0 0 0 0
## *5/*5 1 0 0 0 0 0 0 0
## *5/*9 0 0 1 0 0 0 0 0
## *9/*41 0 0 0 0 1 0 0 0Basic data plots
weight
## country outcome_primary.1 outcome_primary.2
## 1 Brazil 26 156
## 2 Cambodia 50 18
## 3 Colombia 36 11
## 4 Ethiopia 16 25
## 5 India 0 9
## 6 Peru 20 162
## 7 Philippines 0 3
## 8 Thailand 11 56
## 9 Vietnam 7 29## country outcome_primary.1 outcome_primary.2
## 1 Brazil 35 310
## 2 Cambodia 53 36
## 3 Colombia 25 16
## 4 Ethiopia 25 52
## 5 India 4 54
## 6 Peru 30 384
## 7 Philippines 17 6
## 8 Thailand 19 171
## 9 Vietnam 9 44
Methb data
## There are a total of 9632 mthb measurements in 818 patients## Between day 0 and day 20 there are 5816 measurements. Median (range) per patient is 7 (1 to 12)
##
## Call:
## lm(formula = log10(day7_mthb) ~ tqmgkgtot, data = pk_summaries)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.11911 -0.16721 0.00514 0.18448 0.62429
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.100671 0.024584 -4.095 4.76e-05 ***
## tqmgkgtot 0.065552 0.004891 13.404 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.2632 on 648 degrees of freedom
## (72 observations deleted due to missingness)
## Multiple R-squared: 0.2171, Adjusted R-squared: 0.2159
## F-statistic: 179.7 on 1 and 648 DF, p-value: < 2.2e-16
## [1] 17.86515##
## Call:
## lm(formula = t_12_terminal_rescaled ~ AS_score <= 0.5, data = outcome_dat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -9.754 -1.990 -0.422 1.425 33.434
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 18.42601 0.20665 89.166 <2e-16 ***
## AS_score <= 0.5TRUE -0.05197 0.69070 -0.075 0.94
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 3.899 on 389 degrees of freedom
## (709 observations deleted due to missingness)
## Multiple R-squared: 1.455e-05, Adjusted R-squared: -0.002556
## F-statistic: 0.005662 on 1 and 389 DF, p-value: 0.9401
Weight based models of tafenoquine efficacy
## Using all data (n=1073), the odds ratio for recurrence at 4 months for each additional mg/kg of tafenoquine is 0.7 (95% CI 0.65 to 0.75)## Using all data (n=1073), the odds ratio for recurrence at 4 months for each additional mg/kg of primaquine is 0.63 (95% CI 0.55 to 0.71)## Using only patients who got a 300 mg dose (n=469), the odds ratio for recurrence at 4 months for each additional mg/kg of tafenoquine is 0.66 (95% CI 0.51 to 0.85)## Using all patients (n=1073), the odds ratio for recurrence at 6 months for each additional mg/kg of tafenoquine is 0.72 (95% CI 0.67 to 0.77)## Using all patients (n=1073), the odds ratio for recurrence at 6 months for each additional mg/kg of primaquine is 0.61 (95% CI 0.54 to 0.69)EMAX model
load fits
Compare the model fits
Figure 2 in paper: the main mg/kg driving efficacy plot under the EMAX model
## The model estimates that a 15 mg/kg TQ dose reduces 95.75% of all recurrences at 4 months
## 2.5% 50% 97.5%
## 0.5595476 0.6368132 0.7252007
dose-response
## 2.5% 50% 97.5%
## 10.1 15.4 22.3## 2.5% 50% 97.5%
## 4.4 8.0 13.7## 2.5% 50% 97.5%
## 1.9 4.7 10.0Compare for different parts of the world
##
## Africa Americas Asia-Pacific
## 55 724 321## In Americas the odds ratio for recurrence for each additional mg/kg increase in tafenoquine dose is 0.81
## In Asia-Pacific the odds ratio for recurrence for each additional mg/kg increase in tafenoquine dose is 0.82
## In Africa the odds ratio for recurrence for each additional mg/kg increase in tafenoquine dose is 0.81Compare all ORs for logistic regression models
AUC
## Using all data (n=634), the odds ratio for recurrence at 6 months for each additional mg/kg of tafenoquine is 0.6 (95% CI 0.47 to 0.77)## Using patients who got 300 mg (n=469), the odds ratio for recurrence at 6 months for each additional mg/kg of tafenoquine is 0.91 (95% CI 0.7 to 1.13)CMAX
## Using all data (n=634), the odds ratio for recurrence at 6 months for each 10 fold increase in tafenoquine CMAX is 0.15 (95% CI 0.06 to 0.31)## Using who got 300 mg (n=469), the odds ratio for recurrence at 6 months for each 10 fold increase in tafenoquine CMAX is 0.07 (95% CI 0.01 to 0.44)Terminal elimination half-life and efficacy
##
## Call:
## lm(formula = t_12_terminal_rescaled ~ log(weight) + country,
## data = outcome_dat)
##
## Residuals:
## Min 1Q Median 3Q Max
## -9.532 -1.975 -0.385 1.432 33.993
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 9.02208 3.60674 2.501 0.01262 *
## log(weight) 2.11378 0.83738 2.524 0.01183 *
## countryCambodia 0.19427 0.93459 0.208 0.83540
## countryColombia 0.50455 1.07202 0.471 0.63805
## countryEthiopia -0.47763 0.80133 -0.596 0.55135
## countryIndia 0.04244 0.66988 0.063 0.94951
## countryPeru 1.16167 0.40278 2.884 0.00406 **
## countryPhilippines 1.88886 2.17048 0.870 0.38449
## countryThailand 0.02899 0.51722 0.056 0.95533
## countryVietnam 0.30310 0.78000 0.389 0.69771
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 3.715 on 639 degrees of freedom
## (451 observations deleted due to missingness)
## Multiple R-squared: 0.03419, Adjusted R-squared: 0.02059
## F-statistic: 2.514 on 9 and 639 DF, p-value: 0.007827
##
## Pearson's product-moment correlation
##
## data: outcome_dat$weight and outcome_dat$t_12_terminal_rescaled
## t = 3.1948, df = 642, p-value = 0.001468
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.04830372 0.20041913
## sample estimates:
## cor
## 0.1250965## Using all data (n=629), the odds ratio for recurrence at 6 months for each additional day in the tafenoquine half life is 1.15 (95% CI 1.07 to 1.23)## Using all data (n=465), the odds ratio for recurrence at 6 months for each additional day in the tafenoquine half life is 1.17 (95% CI 1.08 to 1.27)Methaemoglobin
##
## Family: binomial
## Link function: logit
##
## Formula:
## outcome_primary ~ s(day7_mthb, k = 3) + tqmgkgtot + s(studysite,
## bs = "re")
##
## Parametric coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -0.27559 0.43874 -0.628 0.52992
## tqmgkgtot -0.28357 0.07931 -3.575 0.00035 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Approximate significance of smooth terms:
## edf Ref.df Chi.sq p-value
## s(day7_mthb) 1.039 1.076 4.168 0.04979 *
## s(studysite) 12.039 19.000 27.830 0.00204 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## R-sq.(adj) = 0.0975 Deviance explained = 12.4%
## UBRE = -0.005556 Scale est. = 1 n = 569## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: binomial ( logit )
## Formula: outcome_primary ~ log(day7_mthb) * tqmgkgtot - day7_mthb + (1 |
## studysite)
## Data: outcome_dat
##
## AIC BIC logLik deviance df.resid
## 773.6 796.5 -381.8 763.6 719
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.3155 -0.6075 -0.3745 0.8231 4.1582
##
## Random effects:
## Groups Name Variance Std.Dev.
## studysite (Intercept) 0.9956 0.9978
## Number of obs: 724, groups: studysite, 20
##
## Fixed effects:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 0.01167 0.31226 0.037 0.97018
## log(day7_mthb) 0.37421 0.23059 1.623 0.10463
## tqmgkgtot -0.31206 0.05551 -5.621 1.9e-08 ***
## log(day7_mthb):tqmgkgtot -0.16305 0.05924 -2.752 0.00592 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) lg(7_) tqmgkg
## lg(dy7_mth) 0.183
## tqmgkgtot -0.437 -0.391
## lg(dy7_mt): -0.060 -0.744 -0.025## Using all data (n=569), the odds ratio for recurrence at 6 months for each absolute percentage increase in methaemoglobin is 0.82 (95% CI 0.67 to 0.98)Everything
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: binomial ( logit )
## Formula: outcome_primary ~ tqmgkgtot * log10(day7_mthb) - log10(day7_mthb) +
## scale(CMAX) + scale(AUC) + scale(t_12_terminal_rescaled) +
## scale(logpara0) + (1 | studysite)
## Data: outcome_dat
##
## AIC BIC logLik deviance df.resid
## 562.7 597.4 -273.4 546.7 558
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -1.7545 -0.5372 -0.3803 -0.1230 3.9730
##
## Random effects:
## Groups Name Variance Std.Dev.
## studysite (Intercept) 0.6069 0.779
## Number of obs: 566, groups: studysite, 20
##
## Fixed effects:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -0.73052 0.55583 -1.314 0.18875
## tqmgkgtot -0.15099 0.11031 -1.369 0.17107
## scale(CMAX) 0.49729 0.58113 0.856 0.39215
## scale(AUC) -0.80410 0.49696 -1.618 0.10566
## scale(t_12_terminal_rescaled) 0.49609 0.16956 2.926 0.00344 **
## scale(logpara0) 0.17300 0.12032 1.438 0.15049
## tqmgkgtot:log10(day7_mthb) -0.21143 0.09744 -2.170 0.03001 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) tqmgkg s(CMAX s(AUC) s(_12_ scl(0)
## tqmgkgtot -0.865
## scale(CMAX) 0.432 -0.405
## scale(AUC) -0.153 0.142 -0.911
## scl(t_12__) 0.055 -0.083 0.644 -0.730
## scal(lgpr0) -0.044 0.028 -0.095 0.062 0.031
## tqmg:10(7_) 0.016 -0.197 -0.295 0.259 -0.056 0.030
Phase 1: relationship with DHA/PQP?
##
## Call:
## glm(formula = log10(day7_mthb) ~ tqmgkgtot + TYPE, data = pk_summaries)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.1253 -0.1679 0.0104 0.1811 0.6181
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.151522 0.036502 -4.151 3.75e-05 ***
## tqmgkgtot 0.064592 0.004908 13.161 < 2e-16 ***
## TYPE 0.062112 0.033011 1.882 0.0603 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for gaussian family taken to be 0.06901405)
##
## Null deviance: 57.344 on 649 degrees of freedom
## Residual deviance: 44.652 on 647 degrees of freedom
## (72 observations deleted due to missingness)
## AIC: 111.87
##
## Number of Fisher Scoring iterations: 2##
## CQ None AL DHA/PQP
## 578 24 24 24Power calculations and trial design
Power calculations
Superiority of 450 over 300 mg single dose